arXiv:1307.5543v3 [nucl-ex] 15 Sep 2014
CERN-PH-EP-2013-134 July 18, 2013
Multi-strange baryon production at mid-rapidity
in Pb–Pb collisions at
√
s
NN= 2.76 TeV
ALICE Collaboration∗
Abstract
The production ofΞ−andΩ−baryons and their anti-particles in Pb–Pb collisions at√sNN= 2.76 TeV has been measured using the ALICE detector. The transverse momentum spectra at mid-rapidity (|y| < 0.5) for chargedΞandΩhyperons have been studied in the range 0.6< pT< 8.0 GeV/c and 1.2< pT< 7.0 GeV/c, respectively, and in several centrality intervals (from the most central 0-10% to the most peripheral 60-80% collisions). These spectra have been compared with the predictions of recent hydrodynamic models. In particular, the Krak ´ow and EPOS models give a satisfactory description of the data, with the latter covering a wider pT range. Mid-rapidity yields, integrated over pT, have been determined. The hyperon-to-pion ratios are similar to those at RHIC: they rise smoothly with centrality up tohNparti ∼ 150 and saturate thereafter. The enhancements (yields per participant nucleon relative to those in pp collisions) increase both with the strangeness content of the baryon and with centrality, but are less pronounced than at lower energies.
PACS numbers: 25.75.Nq, 12.38.Mh, 13.85.Ni, 14.20.Jn
1 Introduction
The study of strange and multi-strange particle production in relativistic heavy-ion collisions is an impor-tant tool to investigate the properties of the strongly interacting system created in the collision. Particle spectra provide information both about the temperature of the system and about collective flow. In par-ticular they reflect conditions at kinetic freeze-out, i.e. the point in the expansion where elastic collisions cease. Collective flow is addressed by hydrodynamic models, and depends on the internal pressure gra-dients created in the collision. The effects are species-dependent, so new data on multi-strange baryons at LHC energies can bring new constraints to models.
The enhancement of strangeness in heavy-ion collisions was one of the earliest proposed signals for the Quark-Gluon Plasma [1, 2, 3]. It rests on the expectation that in a deconfined state the abundances of par-ton species should quickly reach their equilibrium values, resulting in a higher abundance of strangeness per participant than what is seen in proton-proton interactions. In this picture equilibration takes place quickly owing to the low excitation energies required to produce q ¯q pairs. However, it was shown
that, at the same entropy-to-baryon ratio, the plasma in equilibrium does not contain more strangeness than an equilibrated hadron gas at the same temperature [4, 5, 6]. Strangeness enhancements have in-deed been observed by comparing central heavy-ion collisions with p–Be and pp reactions both at the SPS [7, 8, 9, 10, 11, 12] and at RHIC [13, 14, 15]. Over the past 15 years, it has been found that the hadron yields in central heavy-ion collisions follow the expectation for a grand-canonical ensemble [16], increasingly well as a function of the collision energy, indicative of a system in equilibrium. At the same time it was understood that, for pp collisions, canonical suppression effects are important [17] and account for the overall hyperon enhancement. The progressive removal of these effects also quali-tatively describes the increase in strangeness yields with centrality in Pb–Pb, although at RHIC it was noted that canonical suppression could not successfully reproduce all the features of particle produc-tion [18, 19]. At lower energies a better descripproduc-tion of the system size dependencies could be achieved using a core-corona model [20, 21, 22]. These pictures can now be re-examined at the much higher LHC energy. The most straightforward expectation would be equilibrium values for the yields of strange particles in central Pb–Pb collisions, combined with reduced canonical suppression in proton-proton collisions. In this Letter, after an introduction to the ALICE detector and a description of the analysis techniques used to identify strange particles via their decay topology, the multi-strange baryon pTspectra
are presented. Spectra in five different centrality intervals are compared with hydrodynamic models and the corresponding mid-rapidity yields are given. Their ratios to the interpolated yields for pp interactions at the same centre-of-mass energy, normalized to the number of participant nucleons, are used to obtain the enhancement plot as used at lower energies. In addition, we study the dependence on centrality of the hyperon-to-pion production ratio at mid-rapidity and compare these results with predictions.
2 The ALICE experiment
The ALICE experiment was specifically designed to study heavy-ion collisions at the LHC. The ap-paratus consists of a central barrel detector, covering the pseudorapidity window|η| < 0.9, in a large solenoidal magnet providing a 0.5 T field, and a forward dimuon spectrometer with a separate 0.7 T dipole magnet. Additional forward detectors are used for triggering and centrality selection. The first LHC heavy-ion run took place at the end of 2010 with colliding Pb ions accelerated to a centre-of-mass energy per nucleon of√sNN= 2.76 TeV. The analysis described in this paper uses data from this first
heavy-ion run where events in a wide collision centrality range were collected, and is based on the infor-mation provided by the sub-detectors mentioned below.
Tracking and vertexing are performed using the full tracking system. It consists of the Inner Tracking System (ITS), which has six layers of silicon detectors and the Time Projection Chamber (TPC). Three different technologies are used for the ITS: Silicon Pixel Detectors (SPD), Silicon Drift Detectors (SDD)
and Silicon Strip Detectors (SSD). The two innermost layers (at average radii of 3.9 cm and 7.6 cm, covering |η|< 2 and |η|< 1.4, respectively) consist of pixel detectors. These are used to provide high resolution space points (12µm in the plane perpendicular to the beam direction and 100µm along the beam axis). The two intermediate layers consist of silicon drift detectors, and the two outermost layers of double-sided silicon microstrips. Their radii extend from 15 cm to 43 cm and they provide both space points for tracking and energy loss for particle identification. The precise space points provided by the ITS are of great importance in the definition of secondary vertices. The TPC is a large cylindrical drift detector whose active volume extends radially from 85 cm to 247 cm, and from−250 cm to +250 cm along the beam direction. For a charged particle traversing the TPC, up to 159 space points can be recorded. These data are used to calculate a particle trajectory in the magnetic field, and thus determine the track momentum, and also to measure dE/dx information for particle identification.
The SPD layers and the VZERO detector (scintillation hodoscopes placed on either side of the interac-tion region, covering 2.8<η< 5.1 and −3.7 <η< −1.7) are used for triggering. The trigger selec-tion strategy is described in detail in [23]. In addiselec-tion, two neutron Zero Degree Calorimeters (ZDC) positioned at ± 114 m from the interaction point are used in the offline event selection. A complete description of the ALICE sub-detectors can be found in [24].
3 Data samples and cascade reconstruction
The analysis was performed on the full sample recorded during the 2010 Pb–Pb data taking. Only events passing the standard selection for minimum bias events were considered. This selection is mainly based on VZERO and ZDC timing information to reject beam-induced backgrounds and events coming from parasitic beam interactions (“satellite” collisions). The VZERO signal is required to lie in a narrow time window of about 30 ns around the nominal collision time, while a cut in the correlation between the sum and the difference of the arrival times in each of the ZDCs allows to remove satellite events. In addition, a minimal energy deposit of about 500 GeV in the ZDCs is required to further suppress the background from electromagnetic interactions (for details, see [23, 25]). Only events with a primary vertex position within 10 cm from the centre of the detector along the beam line were selected; this ensures good rapidity coverage and uniformity for the particle reconstruction efficiency in the ITS and TPC tracking volume. In order to study the centrality dependence of multi-strange baryon production, these events were divided into five centrality classes according to the fraction of the total inelastic collision cross-section: 0-10%; 10-20%; 20-40%; 40-60%; 60-80%. The definition of the event centrality is based on the sum of the amplitudes measured in the VZERO detectors, as described in [23, 26]. The final sample in the 0-80% centrality range corresponds to approximately 15× 106Pb–Pb collisions at√sNN= 2.76 TeV. For
each centrality class the average number of participant nucleons, hNparti, is calculated from a Glauber
model [26, 27, 28]. This is important for comparisons since the number of participants is often used as a centrality measure at lower energies or in different collision systems.
Multi-strange baryons are measured through the reconstruction of the cascade topology of the follow-ing weak decays into final states with charged particles only: Ξ−→Λ+π− (branching ratio 99.9%) and Ω−→Λ+K− (67.8%) with subsequent decayΛ→ p +π− (63.9%), and their charge conjugates for the anti-particle decays. The resulting branching ratios are 63.9% and 43.3% for theΞand theΩ, respectively. Candidates are found by combining charged tracks reconstructed in the ITS and TPC vol-ume. Topological and kinematic restrictions are imposed, first to select the “V0” (Λcandidate V-shaped decay), and then to match it with one of the remaining secondary tracks (“bachelor” candidate). The dis-tance of closest approach (DCA) between the two V0daughter tracks, or between the V0and the bachelor track, or the V0and the primary vertex position, as well as the V0and cascade candidate pointing angles (PA) with respect to the primary vertex position, are among the most effective selection variables. Pre-defined fiducial windows around the Particle Data Group (PDG) [29] mass values are set, both to select theΛ in the cascade candidates (± 5 MeV/c2) and to reject Ωcandidates that match the Ξhypothesis
(± 8 MeV/c2). In addition, each of the three daughter tracks is checked for compatibility with the pion, kaon or proton hypotheses using their energy loss in the TPC. The selection procedure, while similar to that utilized for the pp sample [30], is optimized for the higher multiplicity environment of the Pb–Pb collisions, which required tightening the cuts on the DCA and PA variables. In particular, all the cuts are fine-tuned in the final analysis, and cross-checked with Monte Carlo simulations, in order to find the best compromise between the combinatorial background minimization and the significance of the signals. The invariant mass distributions of the candidates for all particle species passing the selection cuts are shown in Fig. 1. The signal-to-background ratio, integrated over± 3σ, is 4.1 for theΞand 1.0 for theΩ. The combinatorial background for anti-particles is approximately 5% smaller than for particles, over the whole measured pTrange. This difference has been found to increase rapidly when going to the lowest
momenta, consistent with the different absorption cross sections for baryons and anti-baryons within the detector material. ) 2 c ) (GeV/ π , Λ Invariant Mass( 1.3 1.32 1.34 1.36 2 c Counts / MeV/ 0 100 200 3 10 × = 2.76 TeV NN s Pb-Pb at
-Ξ
+Ξ
0-80% centrality (a) ) 2 c , K ) (GeV/ Λ Invariant Mass( 1.64 1.66 1.68 1.7 2 c Counts / MeV/ 10 15 20 25 30 3 10 × = 2.76 TeV NN s Pb-Pb at-Ω
+Ω
0-80% centrality (b)Fig. 1: Invariant mass distributions for Ξ(a) and Ω (b) selected candidates from 0-80% most central Pb–Pb collisions at√sNN= 2.76 TeV. The plots are for candidates in the rapidity interval|y| < 0.5, at pT> 0.6 and 1.2 GeV/c forΞandΩ, respectively. The arrows point to the PDG mass values.
Data are partitioned into the five centrality bins mentioned above and, for each centrality, into different
pT intervals. To extract the raw yields, a symmetric region around the peak (± 3σ) is defined by fitting
the distribution with the sum of a Gaussian and a polynomial. The background is determined by sampling the regions on both sides of the peak; in these regions, whose width and distance from the peak vary with centrality, pTand particle species, the invariant mass distribution is fitted with a second order polynomial
(first order for high pTbins). The raw yield in each pTand centrality bin is then obtained by subtracting
the integral of the background fit function in the peak region from the total yield in the peak region obtained from bin counting.
A correction factor, which takes into account both the detector acceptance and the reconstruction effi-ciency (including the branching ratio of the measured decay channel), is determined for each particle species as a function of pT, and also in different rapidity intervals to verify that the correction varies by
less than 10% with rapidity. This is true for|y| < 0.5 for all particles with pT > 1.8 GeV/c; for lower
transverse momenta, a narrower rapidity range (|y| < 0.3) has been chosen. Corrections were determined using about 3× 106 Monte Carlo events, generated using HIJING [31] with each event being enriched by one hyperon of each species, generated with a flat pT distribution. The “enriched” events were then
processed with the same reconstruction chain used for the data events. To check that the results are not biased by the presence of such injected signals, the correction computed with the enriched events and that obtained using a “pure” HIJING sample were compared in the low pT region (below 3 GeV/c) and
found to be compatible. Both samples have then been used to maximize the total available statistics for the computation of the correction. As an example, Fig. 2 shows the resulting acceptance× efficiency factors as a function of pT forΞ− and Ω−, both for the most central (0-10%) and the most peripheral
(60-80%) classes. The uncertainties correspond to the total statistics of the Monte Carlo samples used to compute the correction. The curves for the anti-particles are compatible with those for particles. The values are found to decrease with increasing event centrality, as expected. Compared to the correction applied in the 7 TeV pp collision analysis [30], they are smaller by a factor between 2.5 and 3 in the most peripheral class of the Pb–Pb sample, basically because of the tighter selection cuts in the heavy-ion analysis. ) c (GeV/ T p 0 1 2 3 4 5 6 7 8 A c c e p ta n c e x E ff ic ie n c y 0 0.05 0.1 0.15 = 2.76 TeV NN s Pb-Pb at
-Ξ
-Ω
Centrality: 0-10% 60-80% 0-10% x 0.75 60-80% x 0.75Fig. 2: Acceptance× efficiency factors forΞ−(circles) andΩ−(squares) at mid-rapidity as a function of pT, both for the most central 0-10% (full symbols) and the most peripheral 60-80% (open symbols) Pb–Pb collisions. The points already take into account the branching ratios of the corresponding measured decay channels. Those for the
Ω−are also scaled by a factor of 0.75, to avoid overlap with theΞ−at high p T.
4 Corrected spectra and systematic uncertainties
The corrected pT spectra for each particle species were obtained by dividing bin-by-bin the raw yield
distributions by the acceptance× efficiency factors determined as described above. They are shown in Fig. 3 forΞ−,Ξ+,Ω−and Ω+, in the five centrality classes from the most central (0-10%) to the most peripheral (60-80%) Pb–Pb collisions. The values at low pT (below 1.8 GeV/c) have been normalized
to|y| < 0.5 to make all the points correspond to a common rapidity window. Particle and anti-particle spectra are compatible within errors, as expected at LHC energies. The pT interval covered in the most
central collisions spans from 0.6 to 8.0 GeV/c forΞ− and Ξ+, and from 1.2 to 7.0 GeV/c forΩ− and
Ω+
. The transverse momentum range of the measurement is limited by the acceptance at low pTand by
the available statistics at high pT.
In order to extract particle yields integrated over the full pTrange, the spectra are fitted using a blast-wave
parametrisation [32]. Yields are then calculated by adding to the integral of the data in the measured pT
region, the integral of the fit function outside that region. The extrapolation to low pT is a much larger
fraction of the yield than that for high pT: it contributes between 10-20% of the final total yields for theΞ,
and 35-50% forΩ, depending on centrality. Other functions of the transverse momentum (exponential, Boltzmann and Tsallis [33] parametrisations) have been used for comparison with the blast-wave shape. The average difference in the total integrated yield, obtained using the other fit functions, is taken as an estimate of the systematic uncertainty due to the extrapolation: it is found to be around 7% forΞand 15% forΩ, in the worst case of the most peripheral collisions.
The following sources of systematic uncertainty on the final yields have been estimated: i) material budget in the simulation (4%), ii) track selection in the TPC, through the restriction on the number of TPC pad plane clusters used in the particle reconstruction (1% forΞand 3% forΩ), iii) topological and
) c (GeV/ T p 0 1 2 3 4 5 6 7 8 -1 ) c dy) (GeV/ T p N/(d 2 d evts 1/N -4 10 -3 10 -2 10 -1 10 1 10 = 2.76 TeV NN s Pb-Pb at Centrality: 0-10% x 3.0 10-20% x 1.5 20-40% 40-60% 60-80% systematics
-Ξ
(a) ) c (GeV/ T p 0 1 2 3 4 5 6 7 8 -1 ) c dy) (GeV/ T p N/(d 2 d evts 1/N -4 10 -3 10 -2 10 -1 10 1 = 2.76 TeV NN s Pb-Pb at Centrality: 0-10% x 3.0 10-20% x 1.5 20-40% 40-60% 60-80% systematics-Ω
(b) ) c (GeV/ T p 0 1 2 3 4 5 6 7 8 -1 ) c dy) (GeV/ T p N/(d 2 d evts 1/N -4 10 -3 10 -2 10 -1 10 1 10 = 2.76 TeV NN s Pb-Pb at Centrality: 0-10% x 3.0 10-20% x 1.5 20-40% 40-60% 60-80% systematics +Ξ
(c) ) c (GeV/ T p 0 1 2 3 4 5 6 7 8 -1 ) c dy) (GeV/ T p N/(d 2 d evts 1/N -4 10 -3 10 -2 10 -1 10 1 = 2.76 TeV NN s Pb-Pb at Centrality: 0-10% x 3.0 10-20% x 1.5 20-40% 40-60% 60-80% systematics +Ω
(d)Fig. 3: Transverse momentum spectra forΞ−andΩ−(a,b) and their anti-particles (c,d) in five different centrality classes, from the most central (0-10%) to the most peripheral (60-80%) Pb–Pb collisions at√sNN= 2.76 TeV, for
|y| < 0.5 at pT> 1.8 GeV/c and |y| < 0.3 at pT< 1.8 GeV/c. The statistical error bars are smaller than the symbols for most data points, while the systematic uncertainties are represented by the open boxes.
kinematic selection cuts (1% forΞand 3% forΩ), iv) for theΩ, removal of candidates satisfying theΞ mass hypothesis (1%), v) signal extraction procedure (1%), vi) use of FLUKA [34] to correct [35] the anti-proton absorption cross section in GEANT3 [36] (1%), vii) centrality dependence of the correction (3%). The last contribution is related to the fact that the particle distributions in a given centrality class are different in the injected Monte Carlo simulations and in the data. The total systematic uncertainty, obtained by adding the sources above in quadrature, is 5% forΞand 7% forΩ, independent of the pTbin
and centrality interval. It has been added in quadrature to the statistical error for each spectra data point before fitting the distribution and extracting the yields. An additional systematic error of 7% (15%) has been added to the finalΞ(Ω) yield to take into account the uncertainty due to the extrapolation at low
pT, as mentioned above.
5 Results and discussion
The total integrated yields forΞ−, Ξ+, Ξ−+ Ξ+, Ω−, Ω+ andΩ−+Ω+ have been determined in each centrality class, and are presented in Table 1. Statistical and systematic uncertainties are quoted. The systematic errors include both the contribution due to the correction factors and that from the extrapola-tion to the unmeasured pTregion. Particle and anti-particle yields are found to be compatible within the
errors.
TheΞandΩ pT spectra are compared to hydrodynamic model calculations. The purpose of this
com-parison is to test the ability of the models to reproduce yields, spectral shape and centrality dependence. Four models are considered. VISH2+1 [37] is a viscous hydrodynamic model, while HKM [38, 39]
Table 1: Total integrated mid-rapidity yields, dN/dy, for multi-strange baryons in Pb–Pb collisions at√sNN= 2.76 TeV, for different centrality intervals. Both statistical (first) and systematic (second) errors are shown. For each centrality interval the average number of participants,hNparti, is also reported [26].
Centrality 0-10% 10-20% 20-40% 40-60% 60-80% hNparti 356.1± 3.6 260.1± 3.9 157.2± 3.1 68.6± 2.0 22.5± 0.8 Ξ− 3.34± 0.06 ± 0.24 2.53± 0.04 ± 0.18 1.49± 0.02 ± 0.11 0.53± 0.01 ± 0.04 0.124± 0.003 ± 0.009 Ξ+ 3.28± 0.06 ± 0.23 2.51± 0.05 ± 0.18 1.53± 0.02 ± 0.11 0.54± 0.01 ± 0.04 0.120± 0.003 ± 0.008 Ξ−+Ξ+ 6.67± 0.08 ± 0.47 5.14± 0.06 ± 0.36 3.03± 0.03 ± 0.22 1.07± 0.01 ± 0.08 0.240± 0.006 ± 0.019 Ω− 0.58± 0.04 ± 0.09 0.37± 0.03 ± 0.06 0.23± 0.01 ± 0.03 0.087± 0.005 ± 0.014 0.015± 0.002 ± 0.003 Ω+ 0.60± 0.05 ± 0.09 0.40± 0.03 ± 0.06 0.25± 0.01 ± 0.03 0.082± 0.005 ± 0.013 0.017± 0.002 ± 0.003 Ω−+Ω+ 1.19± 0.06 ± 0.19 0.78± 0.04 ± 0.15 0.48± 0.02 ± 0.08 0.170± 0.007 ± 0.029 0.032± 0.003 ± 0.005
is an ideal hydrodynamic model similar to VISH2+1 which, in addition, introduces a hadronic cascade (UrQMD [40, 41]) following the partonic hydrodynamic phase. The Krak´ow model [42, 43], on the other hand, introduces non-equilibrium corrections due to viscosity in the transition from a hydrody-namic description to one involving the final state particles. EPOS (2.17v3) [44, 45, 46] aims to be a comprehensive model and event generator, describing all pTdomains with the same dynamical picture:
in particular, it incorporates hydrodynamics and models the interaction between high pThadrons and the
expanding fluid, then uses UrQMD as hadronic cascade model.
The results are shown in Fig. 4 forΞandΩhyperons in different ranges of centrality. Predictions in each of the data centrality intervals are available for all the models, except for HKM, which is available only for the 10-20% and 20-40% most central collisions. Moreover, for EPOS the curves correspond to the average of particle and anti-particle as for the data points, while for the other models only the predictions for theΞ−andΩ−are available at the time of writing.
We first focus on the most central events (0-10%). Here, all the available models succeed in describing the shape of theΞspectrum quite well in the pT range up to 3 GeV/c, although only the Krak´ow model
correctly reproduces the yield. This supports the hydrodynamic interpretation of the pTspectra in central
collisions at the LHC, which was already shown to be successful in describing pion, kaon and proton spectra [47]. The description is less successful with theΩ. VISH2+1 and EPOS both overestimate the yield, though EPOS reproduces the shape; Krak´ow underestimates the yield and does not reproduce the slope. As we move progressively to less central events, the quality of the agreement remains similar for theΞ, but deteriorates for theΩ. For theΞ, the Krak´ow model describes both the yield and the shape to within about 30% over the centrality range 0-60%, while it fails to describe the spectrum in the most peripheral class. EPOS describes the shape correctly for all centralities and also reproduces the yield in the most peripheral class, while the other two models give a worse description. For theΩ, the EPOS and Krak´ow models again provide the most successful description, reproducing the shape rather well (i.e. to within∼ 30%) in all the centrality classes, although EPOS consistently overestimates the yields. As in the case of theΞ, VISH2+1 and HKM provide a less accurate description of the data, though HKM works better than VISH2+1. Comparing these models gives an insight into the mechanism at work in hyperon production. VISH2+1, which results in the least successful description, does not include the hadronic cascade mechanism. The Krak´ow model indeed provides a good description for both the yields and shapes in the pT range up to 3 GeV/c. EPOS, on the other hand, includes all these processes and
gives the most successful description overall in a wider pTrange. In this model the aim is to account in
a single approach for bulk matter and jets, and the interaction between the two; the flux-tubes produced in the initial hard scattering either escape the medium and hadronize as jets, or contribute to the bulk matter where hydrodynamics becomes important. Good agreement has already been observed between EPOS and ALICE data for pion, kaon and proton spectra in central and semi-central collisions [47]; in this study the agreement is confirmed for theΞandΩhyperons, and extended to peripheral events.
0 1 2 3 4 5 6 7 8 -1 ) c dy) (GeV/ T p N/(d 2 d evts 1/N -4 10 -3 10 -2 10 -1 10 1 10 = 2.76 TeV NN s Pb-Pb at (a) Centrality: 0-10% x 3.0 10-20% x 1.5 20-40% 40-60% 60-80% systematics
Ξ
VISH2+1 EPOS HKM w o Krak 0 1 2 3 4 5 6 7 8 -1) c dy) (GeV/ T p N/(d 2 d evts 1/N -4 10 -3 10 -2 10 -1 10 1 = 2.76 TeV NN s Pb-Pb at (b) Centrality: 0-10% x 3.0 10-20% x 1.5 20-40% 40-60% 60-80% systematicsΩ
VISH2+1 EPOS HKM w o Krak / Data 1 2 3 0-10% Model 1 2 3 10-20% 1 2 3 20-40% 1 2 3 40-60% ) c (GeV/ T p 0 1 2 3 4 5 6 7 8 1 2 3 60-80% / Data 1 2 3 0-10% Model 1 2 3 10-20% 1 2 3 20-40% 1 2 3 40-60% ) c (GeV/ T p 0 1 2 3 4 5 6 7 8 1 2 3 60-80%Fig. 4: Transverse momentum spectra forΞ(a) andΩ(b) hyperons (average of particle and anti-particle) in five different centrality classes, compared to hydrodynamic models. Ratios of models to data are also shown.
The strangeness enhancements are defined as ratios of the strange particle yields measured in Pb–Pb collisions, normalized to the mean number of participant nucleonshNparti, to the corresponding quantities
in pp interactions at the same energy. The pp reference values were obtained by interpolating ALICE data at two energies (√s = 0.9 and 7 TeV [30, 48]) for theΞ, and STAR data at 200 GeV [49] and ALICE data at 7 TeV for theΩ. For both particles, the energy dependence of the PYTHIA yields3 is assumed. Although PYTHIA underestimates the overall yields [30, 51], its energy dependence is found to be s0.13 (which is slightly higher than s0.11, obtained for the charged-particle pseudorapidity density [25]): the same power law describes the measured yields and is therefore used for interpolation.
Figure 5a and b show the enhancements forΞ−,Ξ+andΩ−+Ω+in Pb–Pb collisions at√sNN= 2.76 TeV
(full symbols), as a function of the mean number of participants. For the Ω, particle and anti-particle have been added for the sake of comparison with the corresponding results at lower energy. The en-hancements are larger than unity for all the particles. They increase with the strangeness content of the particle, showing the hierarchy already observed at lower energies and also consistent with the picture of enhanced ss pair production in a hot and dense partonic medium. In addition, the same shape and scale are observed for baryons and anti-baryons (shown forΞ− andΞ+ in Fig. 5), as expected because of the vanishing net-baryon number at the LHC energy. The centrality dependence shows that the multi-strange particle yields grow faster than linearly withhNparti, at least up to the three most central classes
(Npart > 100-150), where there are indications of a possible saturation of the enhancements.
Compar-ing the ALICE measurements with those from the experiments NA57 at the SPS (Pb–Pb collisions at √s
NN= 17.2 GeV) and STAR at RHIC (Au–Au collisions at√sNN= 200 GeV), represented by the open
symbols in Fig. 5a and b, the enhancements are found to decrease with increasing centre-of-mass energy, continuing the trend established at lower energies [8, 9, 15].
The hyperon-to-pion ratiosΞ/π ≡ (Ξ−+Ξ+
)/(π−+π+
) andΩ/π ≡ (Ω−+Ω+
)/(π−+π+
), for A–A and pp collisions both at LHC [30, 47, 48, 52, 53] and RHIC [49, 54, 14] energies, are shown in Fig. 5c as a function ofhNparti. They indicate that different mechanisms contribute to the evolution with centrality
of the enhancements as defined above. Indeed, the relative production of strangeness in pp collisions is larger than at lower energies. The increase in the hyperon-to-pion ratios in A–A relative to pp (∼ 1.6 and 3.3 forΞandΩ, respectively) is about half that of the standard enhancement ratio as defined above. It displays a clear increase in strangeness production relative to pp, rising with centrality up to about hNparti ∼ 150, and apparently saturating thereafter. A small drop is observed in theΞ/πratio for the most
central collisions, which is however of limited significance given the size of the systematic errors. Also shown are the predictions for the hyperon-to-pion ratios at the LHC from the thermal models, based on a grand canonical approach, described in [55] (full line, with a chemical freeze-out temperature parameter
T = 164 MeV) and [56] (dashed line, with T = 170 MeV). We note that the predictions for T = 164 MeV
agree with the present data while, for this temperature, the proton-to-pion ratio is overpredicted by about 50% [47]. It is now an interesting question whether a grand-canonical thermal model can give a good de-scription of the complete set of hadron yields in Pb–Pb collisions at LHC energy with a somewhat lower
T value. Alternatively, the low p/πratio has been addressed in three different approaches: i) suppression governed by light quark fugacity in a non-equilibrium model [57, 58], ii) baryon-antibaryon annihila-tion in the hadronic phase, which would have a stronger effect on protons than on multi-strange par-ticles [59, 60, 61, 62], iii) effects due to pre-hadronic flavour-dependent bound states above the QCD transition temperature [63, 64]. 〉 part N 〈 1 10 102 relative to pp/p-Be 〉 part N 〈 Y ie ld / 1 10 = 2.76 TeV NN s Pb-Pb at -Ξ NA57 Pb-Pb, p-Pb at 17.2 GeV STAR Au-Au at 200 GeV (a) 〉 part N 〈 1 10 102 relative to pp/p-Be 〉 part N 〈 Y ie ld / 1 10 + Ω + -Ω + Ξ NA57 Pb-Pb, p-Pb at 17.2 GeV STAR Au-Au at 200 GeV (b) 〉 part N 〈 1 10 102 Hyperon-to-pion ratio -4 10 -3 10 π / Ξ π / Ω ALICE Pb-Pb at 2.76 TeV ALICE pp at 7 TeV ALICE pp at 900 GeV STAR Au-Au, pp at 200 GeV ALICE Pb-Pb at 2.76 TeV ALICE pp at 7 TeV STAR Au-Au, pp at 200 GeV (c)
Fig. 5: (a,b) Enhancements in the rapidity range|y| < 0.5 as a function of the mean number of participants hNparti, showing LHC (ALICE, full symbols), RHIC and SPS (open symbols) data. The LHC data use interpolated pp values (see text). Boxes on the dashed line at unity indicate statistical and systematic uncertainties on the pp or p–Be reference. Error bars on the data points represent the corresponding uncertainties for all the heavy-ion measurements and those for p–Pb at the SPS. (c) Hyperon-to-pion ratios as a function ofhNparti, for A–A and pp collisions at LHC and RHIC energies. The lines mark the thermal model predictions from [55] (full line) and [56] (dashed line).
6 Conclusions
In summary, the measurement of multi-strange baryon production in heavy-ion collisions at the LHC and the corresponding strangeness enhancements with respect to pp have been presented. Transverse momentum spectra of mid-rapidityΞ−,Ξ+,Ω−andΩ+particles in Pb–Pb collisions at√sNN= 2.76 TeV
several hydrodynamic models. It is found that the best agreements are obtained with the Krak´ow and EPOS models, with the latter covering a wider pT range. The yields have been measured to be larger
than at RHIC while the hyperon-to-pion ratios are similar at the two energies, rising with centrality and showing a saturation athNparti ∼ 150. The values of those ratios for central collisions are found
compatible with recent predictions from thermal models. The enhancements relative to pp increase both with the strangeness content of the baryon and with centrality, but are less pronounced than at lower energies.
Acknowledgements
The ALICE collaboration would like to thank all its engineers and technicians for their invaluable con-tributions to the construction of the experiment and the CERN accelerator teams for the outstanding performance of the LHC complex.
The ALICE collaboration acknowledges the following funding agencies for their support in building and running the ALICE detector:
State Committee of Science, World Federation of Scientists (WFS) and Swiss Fonds Kidagan, Armenia, Conselho Nacional de Desenvolvimento Cient´ıfico e Tecnol´ogico (CNPq), Financiadora de Estudos e Projetos (FINEP), Fundac¸˜ao de Amparo `a Pesquisa do Estado de S˜ao Paulo (FAPESP);
National Natural Science Foundation of China (NSFC), the Chinese Ministry of Education (CMOE) and the Ministry of Science and Technology of China (MSTC);
Ministry of Education and Youth of the Czech Republic;
Danish Natural Science Research Council, the Carlsberg Foundation and the Danish National Research Foundation;
The European Research Council under the European Community’s Seventh Framework Programme; Helsinki Institute of Physics and the Academy of Finland;
French CNRS-IN2P3, the ‘Region Pays de Loire’, ‘Region Alsace’, ‘Region Auvergne’ and CEA, France;
German BMBF and the Helmholtz Association;
General Secretariat for Research and Technology, Ministry of Development, Greece; Hungarian OTKA and National Office for Research and Technology (NKTH);
Department of Atomic Energy and Department of Science and Technology of the Government of India; Istituto Nazionale di Fisica Nucleare (INFN) and Centro Fermi - Museo Storico della Fisica e Centro Studi e Ricerche ”Enrico Fermi”, Italy;
MEXT Grant-in-Aid for Specially Promoted Research, Japan; Joint Institute for Nuclear Research, Dubna;
National Research Foundation of Korea (NRF);
CONACYT, DGAPA, M´exico, ALFA-EC and the EPLANET Program (European Particle Physics Latin American Network)
Stichting voor Fundamenteel Onderzoek der Materie (FOM) and the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO), Netherlands;
Research Council of Norway (NFR);
Polish Ministry of Science and Higher Education;
National Authority for Scientific Research NASR (Autoritatea Nat¸ional˘a pentru Cercetare S¸tiint¸ific˘a -ANCS);
Ministry of Education and Science of Russian Federation, Russian Academy of Sciences, Russian Fed-eral Agency of Atomic Energy, Russian FedFed-eral Agency for Science and Innovations and The Russian Foundation for Basic Research;
Ministry of Education of Slovakia;
Department of Science and Technology, South Africa;
(Conseller´ıa de Educaci´on), CEADEN, Cubaenerg´ıa, Cuba, and IAEA (International Atomic Energy Agency);
Swedish Research Council (VR) and Knut & Alice Wallenberg Foundation (KAW); Ukraine Ministry of Education and Science;
United Kingdom Science and Technology Facilities Council (STFC);
The United States Department of Energy, the United States National Science Foundation, the State of Texas, and the State of Ohio.
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S. Nazarenko92, A. Nedosekin53, M. Nicassio90 ,30, M. Niculescu33 ,57, B.S. Nielsen74, S. Nikolaev93, S. Nikulin93, V. Nikulin79, B.S. Nilsen80, M.S. Nilsson20, F. Noferini11 ,98, P. Nomokonov61, G. Nooren52, A. Nyanin93, A. Nyatha42, J. Nystrand17, H. Oeschler86 ,47, S.K. Oh39 ,iv, S. Oh125, L. Olah124, J. Oleniacz122, A.C. Oliveira Da Silva111, J. Onderwaater90, C. Oppedisano104, A. Ortiz Velasquez31, A. Oskarsson31,
J. Otwinowski90, K. Oyama86, Y. Pachmayer86, M. Pachr36, P. Pagano28, G. Pai´c58, F. Painke38, C. Pajares15, S.K. Pal120, A. Palaha95, A. Palmeri100, V. Papikyan1, G.S. Pappalardo100, W.J. Park90, A. Passfeld48, D.I. Patalakha50, V. Paticchio97, B. Paul94, T. Pawlak122, T. Peitzmann52, H. Pereira Da Costa13,
E. Pereira De Oliveira Filho111, D. Peresunko93, C.E. P´erez Lara75, D. Perrino30, W. Peryt122 ,i, A. Pesci98, Y. Pestov4, V. Petr´aˇcek36, M. Petran36, M. Petris72, P. Petrov95, M. Petrovici72, C. Petta26, S. Piano103, M. Pikna35, P. Pillot105, O. Pinazza33 ,98, L. Pinsky113, N. Pitz46, D.B. Piyarathna113, M. Planinic91,
M. Płosko ´n68, J. Pluta122, S. Pochybova124, P.L.M. Podesta-Lerma110, M.G. Poghosyan33, B. Polichtchouk50, A. Pop72, S. Porteboeuf-Houssais64, V. Posp´ıˇsil36, B. Potukuchi84, S.K. Prasad123, R. Preghenella11 ,98, F. Prino104, C.A. Pruneau123, I. Pshenichnov51, G. Puddu21, V. Punin92, J. Putschke123, H. Qvigstad20, A. Rachevski103, A. Rademakers33, J. Rak114, A. Rakotozafindrabe13, L. Ramello29, S. Raniwala85, R. Raniwala85, S.S. R¨as¨anen40, B.T. Rascanu46, D. Rathee81, W. Rauch33, A.W. Rauf14, V. Razazi21, K.F. Read115, J.S. Real65, K. Redlich71 ,v, R.J. Reed125, A. Rehman17, P. Reichelt46, M. Reicher52, F. Reidt33 ,86, R. Renfordt46, A.R. Reolon66, A. Reshetin51, F. Rettig38, J.-P. Revol33, K. Reygers86, L. Riccati104, R.A. Ricci67, T. Richert31, M. Richter20, P. Riedler33, W. Riegler33, F. Riggi26, A. Rivetti104, M. Rodr´ıguez Cahuantzi2, A. Rodriguez Manso75, K. Røed17 ,20, E. Rogochaya61, S. Rohni84, D. Rohr38, D. R¨ohrich17, R. Romita76 ,90, F. Ronchetti66, P. Rosnet64, S. Rossegger33, A. Rossi33, P. Roy94, C. Roy49, A.J. Rubio Montero9, R. Rui22, R. Russo23, E. Ryabinkin93, A. Rybicki108, S. Sadovsky50, K. ˇSafaˇr´ık33, R. Sahoo43, P.K. Sahu56, J. Saini120, H. Sakaguchi41, S. Sakai68 ,66, D. Sakata117, C.A. Salgado15, J. Salzwedel18, S. Sambyal84, V. Samsonov79, X. Sanchez Castro58 ,49, L. ˇS´andor54, A. Sandoval59, M. Sano117, G. Santagati26, R. Santoro11 ,33, D. Sarkar120, E. Scapparone98, F. Scarlassara27, R.P. Scharenberg88, C. Schiaua72, R. Schicker86, C. Schmidt90, H.R. Schmidt32, S. Schuchmann46,
J. Schukraft33, M. Schulc36, T. Schuster125, Y. Schutz33 ,105, K. Schwarz90, K. Schweda90, G. Scioli25, E. Scomparin104, R. Scott115, P.A. Scott95, G. Segato27, I. Selyuzhenkov90, J. Seo89, S. Serci21,
E. Serradilla9 ,59, A. Sevcenco57, A. Shabetai105, G. Shabratova61, R. Shahoyan33, S. Sharma84, N. Sharma115, K. Shigaki41, K. Shtejer8, Y. Sibiriak93, S. Siddhanta99, T. Siemiarczuk71, D. Silvermyr78, C. Silvestre65, G. Simatovic91, R. Singaraju120, R. Singh84, S. Singha120, V. Singhal120, B.C. Sinha120, T. Sinha94, B. Sitar35, M. Sitta29, T.B. Skaali20, K. Skjerdal17, R. Smakal36, N. Smirnov125, R.J.M. Snellings52, R. Soltz69,
M. Song126, J. Song89, C. Soos33, F. Soramel27, M. Spacek36, I. Sputowska108, M. Spyropoulou-Stassinaki82, B.K. Srivastava88, J. Stachel86, I. Stan57, G. Stefanek71, M. Steinpreis18, E. Stenlund31, G. Steyn60,
J.H. Stiller86, D. Stocco105, M. Stolpovskiy50, P. Strmen35, A.A.P. Suaide111, M.A. Subieta V´asquez23, T. Sugitate41, C. Suire44, M. Suleymanov14, R. Sultanov53, M. ˇSumbera77, T. Susa91, T.J.M. Symons68, A. Szanto de Toledo111, I. Szarka35, A. Szczepankiewicz33, M. Szyma´nski122, J. Takahashi112,
M.A. Tangaro30, J.D. Tapia Takaki44, A. Tarantola Peloni46, A. Tarazona Martinez33, A. Tauro33, G. Tejeda Mu ˜noz2, A. Telesca33, C. Terrevoli30, A. Ter Minasyan93 ,70, J. Th¨ader90, D. Thomas52, R. Tieulent118, A.R. Timmins113, A. Toia101, H. Torii116, V. Trubnikov3, W.H. Trzaska114, T. Tsuji116, A. Tumkin92, R. Turrisi101, T.S. Tveter20, J. Ulery46, K. Ullaland17, J. Ulrich45, A. Uras118, G.M. Urciuoli102, G.L. Usai21, M. Vajzer77, M. Vala54 ,61, L. Valencia Palomo44, P. Vande Vyvre33, L. Vannucci67,
J.W. Van Hoorne33, M. van Leeuwen52, A. Vargas2, R. Varma42, M. Vasileiou82, A. Vasiliev93,
V. Vechernin119, M. Veldhoen52, M. Venaruzzo22, E. Vercellin23, S. Vergara2, R. Vernet7, M. Verweij123 ,52, L. Vickovic107, G. Viesti27, J. Viinikainen114, Z. Vilakazi60, O. Villalobos Baillie95, A. Vinogradov93, L. Vinogradov119, Y. Vinogradov92, T. Virgili28, Y.P. Viyogi120, A. Vodopyanov61, M.A. V¨olkl86,
S. Voloshin123, K. Voloshin53, G. Volpe33, B. von Haller33, I. Vorobyev119, D. Vranic33 ,90, J. Vrl´akov´a37, B. Vulpescu64, A. Vyushin92, B. Wagner17, V. Wagner36, J. Wagner90, Y. Wang86, Y. Wang6, M. Wang6, D. Watanabe117, K. Watanabe117, M. Weber113, J.P. Wessels48, U. Westerhoff48, J. Wiechula32, J. Wikne20, M. Wilde48, G. Wilk71, J. Wilkinson86, M.C.S. Williams98, B. Windelband86, M. Winn86, C. Xiang6, C.G. Yaldo123, Y. Yamaguchi116, H. Yang13 ,52, P. Yang6, S. Yang17, S. Yano41, S. Yasnopolskiy93, J. Yi89, Z. Yin6, I.-K. Yoo89, I. Yushmanov93, V. Zaccolo74, C. Zach36, C. Zampolli98, S. Zaporozhets61,
A. Zarochentsev119, P. Z´avada55, N. Zaviyalov92, H. Zbroszczyk122, P. Zelnicek45, I.S. Zgura57, M. Zhalov79, F. Zhang6, Y. Zhang6, H. Zhang6, X. Zhang68 ,64 ,6, D. Zhou6, Y. Zhou52, F. Zhou6, X. Zhu6, J. Zhu6, J. Zhu6, H. Zhu6, A. Zichichi11 ,25, M.B. Zimmermann48 ,33, A. Zimmermann86, G. Zinovjev3, Y. Zoccarato118, M. Zynovyev3, M. Zyzak46
Affiliation notes
iDeceased
iiAlso at: M.V.Lomonosov Moscow State University, D.V.Skobeltsyn Institute of Nuclear Physics, Moscow, Russia
iiiAlso at: University of Belgrade, Faculty of Physics and ”Vinˇca” Institute of Nuclear Sciences, Belgrade, Serbia
ivPermanent address: Konkuk University, Seoul, Korea
vAlso at: Institute of Theoretical Physics, University of Wroclaw, Wroclaw, Poland
Collaboration Institutes
1 A. I. Alikhanyan National Science Laboratory (Yerevan Physics Institute) Foundation, Yerevan, Armenia 2 Benem´erita Universidad Aut´onoma de Puebla, Puebla, Mexico
3 Bogolyubov Institute for Theoretical Physics, Kiev, Ukraine 4 Budker Institute for Nuclear Physics, Novosibirsk, Russia
5 California Polytechnic State University, San Luis Obispo, California, United States 6 Central China Normal University, Wuhan, China
7 Centre de Calcul de l’IN2P3, Villeurbanne, France
8 Centro de Aplicaciones Tecnol´ogicas y Desarrollo Nuclear (CEADEN), Havana, Cuba
9 Centro de Investigaciones Energ´eticas Medioambientales y Tecnol´ogicas (CIEMAT), Madrid, Spain 10 Centro de Investigaci´on y de Estudios Avanzados (CINVESTAV), Mexico City and M´erida, Mexico 11 Centro Fermi - Museo Storico della Fisica e Centro Studi e Ricerche “Enrico Fermi”, Rome, Italy 12 Chicago State University, Chicago, United States
13 Commissariat `a l’Energie Atomique, IRFU, Saclay, France
15 Departamento de F´ısica de Part´ıculas and IGFAE, Universidad de Santiago de Compostela, Santiago de Compostela, Spain
16 Department of Physics Aligarh Muslim University, Aligarh, India
17 Department of Physics and Technology, University of Bergen, Bergen, Norway 18 Department of Physics, Ohio State University, Columbus, Ohio, United States 19 Department of Physics, Sejong University, Seoul, South Korea
20 Department of Physics, University of Oslo, Oslo, Norway
21 Dipartimento di Fisica dell’Universit`a and Sezione INFN, Cagliari, Italy 22 Dipartimento di Fisica dell’Universit`a and Sezione INFN, Trieste, Italy 23 Dipartimento di Fisica dell’Universit`a and Sezione INFN, Turin, Italy
24 Dipartimento di Fisica dell’Universit`a ‘La Sapienza‘ and Sezione INFN, Rome, Italy 25 Dipartimento di Fisica e Astronomia dell’Universit`a and Sezione INFN, Bologna, Italy 26 Dipartimento di Fisica e Astronomia dell’Universit`a and Sezione INFN, Catania, Italy 27 Dipartimento di Fisica e Astronomia dell’Universit`a and Sezione INFN, Padova, Italy
28 Dipartimento di Fisica ‘E.R. Caianiello’ dell’Universit`a and Gruppo Collegato INFN, Salerno, Italy 29 Dipartimento di Scienze e Innovazione Tecnologica dell’Universit`a del Piemonte Orientale and Gruppo
Collegato INFN, Alessandria, Italy
30 Dipartimento Interateneo di Fisica ‘M. Merlin’ and Sezione INFN, Bari, Italy 31 Division of Experimental High Energy Physics, University of Lund, Lund, Sweden 32 Eberhard Karls Universit¨at T¨ubingen, T¨ubingen, Germany
33 European Organization for Nuclear Research (CERN), Geneva, Switzerland 34 Faculty of Engineering, Bergen University College, Bergen, Norway
35 Faculty of Mathematics, Physics and Informatics, Comenius University, Bratislava, Slovakia
36 Faculty of Nuclear Sciences and Physical Engineering, Czech Technical University in Prague, Prague, Czech Republic
37 Faculty of Science, P.J. ˇSaf´arik University, Koˇsice, Slovakia
38 Frankfurt Institute for Advanced Studies, Johann Wolfgang Goethe-Universit¨at Frankfurt, Frankfurt, Germany
39 Gangneung-Wonju National University, Gangneung, South Korea 40 Helsinki Institute of Physics (HIP), Helsinki, Finland
41 Hiroshima University, Hiroshima, Japan
42 Indian Institute of Technology Bombay (IIT), Mumbai, India 43 Indian Institute of Technology Indore, India (IITI)
44 Institut de Physique Nucl´eaire d’Orsay (IPNO), Universit´e Paris-Sud, CNRS-IN2P3, Orsay, France 45 Institut f¨ur Informatik, Johann Wolfgang Goethe-Universit¨at Frankfurt, Frankfurt, Germany 46 Institut f¨ur Kernphysik, Johann Wolfgang Goethe-Universit¨at Frankfurt, Frankfurt, Germany 47 Institut f¨ur Kernphysik, Technische Universit¨at Darmstadt, Darmstadt, Germany
48 Institut f¨ur Kernphysik, Westf¨alische Wilhelms-Universit¨at M¨unster, M¨unster, Germany
49 Institut Pluridisciplinaire Hubert Curien (IPHC), Universit´e de Strasbourg, CNRS-IN2P3, Strasbourg, France
50 Institute for High Energy Physics, Protvino, Russia
51 Institute for Nuclear Research, Academy of Sciences, Moscow, Russia 52 Institute for Subatomic Physics of Utrecht University, Utrecht, Netherlands 53 Institute for Theoretical and Experimental Physics, Moscow, Russia
54 Institute of Experimental Physics, Slovak Academy of Sciences, Koˇsice, Slovakia
55 Institute of Physics, Academy of Sciences of the Czech Republic, Prague, Czech Republic 56 Institute of Physics, Bhubaneswar, India
57 Institute of Space Science (ISS), Bucharest, Romania
58 Instituto de Ciencias Nucleares, Universidad Nacional Aut´onoma de M´exico, Mexico City, Mexico 59 Instituto de F´ısica, Universidad Nacional Aut´onoma de M´exico, Mexico City, Mexico
60 iThemba LABS, National Research Foundation, Somerset West, South Africa 61 Joint Institute for Nuclear Research (JINR), Dubna, Russia
62 Korea Institute of Science and Technology Information, Daejeon, South Korea 63 KTO Karatay University, Konya, Turkey
64 Laboratoire de Physique Corpusculaire (LPC), Clermont Universit´e, Universit´e Blaise Pascal, CNRS–IN2P3, Clermont-Ferrand, France
65 Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Universit´e Joseph Fourier, CNRS-IN2P3, Institut Polytechnique de Grenoble, Grenoble, France
66 Laboratori Nazionali di Frascati, INFN, Frascati, Italy 67 Laboratori Nazionali di Legnaro, INFN, Legnaro, Italy
68 Lawrence Berkeley National Laboratory, Berkeley, California, United States 69 Lawrence Livermore National Laboratory, Livermore, California, United States 70 Moscow Engineering Physics Institute, Moscow, Russia
71 National Centre for Nuclear Studies, Warsaw, Poland
72 National Institute for Physics and Nuclear Engineering, Bucharest, Romania 73 National Institute of Science Education and Research, Bhubaneswar, India 74 Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark 75 Nikhef, National Institute for Subatomic Physics, Amsterdam, Netherlands 76 Nuclear Physics Group, STFC Daresbury Laboratory, Daresbury, United Kingdom
77 Nuclear Physics Institute, Academy of Sciences of the Czech Republic, ˇReˇz u Prahy, Czech Republic 78 Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States
79 Petersburg Nuclear Physics Institute, Gatchina, Russia
80 Physics Department, Creighton University, Omaha, Nebraska, United States 81 Physics Department, Panjab University, Chandigarh, India
82 Physics Department, University of Athens, Athens, Greece
83 Physics Department, University of Cape Town, Cape Town, South Africa 84 Physics Department, University of Jammu, Jammu, India
85 Physics Department, University of Rajasthan, Jaipur, India
86 Physikalisches Institut, Ruprecht-Karls-Universit¨at Heidelberg, Heidelberg, Germany 87 Politecnico di Torino, Turin, Italy
88 Purdue University, West Lafayette, Indiana, United States 89 Pusan National University, Pusan, South Korea
90 Research Division and ExtreMe Matter Institute EMMI, GSI Helmholtzzentrum f¨ur Schwerionenforschung, Darmstadt, Germany
91 Rudjer Boˇskovi´c Institute, Zagreb, Croatia
92 Russian Federal Nuclear Center (VNIIEF), Sarov, Russia 93 Russian Research Centre Kurchatov Institute, Moscow, Russia 94 Saha Institute of Nuclear Physics, Kolkata, India
95 School of Physics and Astronomy, University of Birmingham, Birmingham, United Kingdom 96 Secci´on F´ısica, Departamento de Ciencias, Pontificia Universidad Cat´olica del Per´u, Lima, Peru 97 Sezione INFN, Bari, Italy
98 Sezione INFN, Bologna, Italy 99 Sezione INFN, Cagliari, Italy 100 Sezione INFN, Catania, Italy 101 Sezione INFN, Padova, Italy 102 Sezione INFN, Rome, Italy 103 Sezione INFN, Trieste, Italy 104 Sezione INFN, Turin, Italy
105 SUBATECH, Ecole des Mines de Nantes, Universit´e de Nantes, CNRS-IN2P3, Nantes, France 106 Suranaree University of Technology, Nakhon Ratchasima, Thailand
107 Technical University of Split FESB, Split, Croatia
108 The Henryk Niewodniczanski Institute of Nuclear Physics, Polish Academy of Sciences, Cracow, Poland 109 The University of Texas at Austin, Physics Department, Austin, TX, United States
110 Universidad Aut´onoma de Sinaloa, Culiac´an, Mexico 111 Universidade de S˜ao Paulo (USP), S˜ao Paulo, Brazil
112 Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil 113 University of Houston, Houston, Texas, United States
114 University of Jyv¨askyl¨a, Jyv¨askyl¨a, Finland
115 University of Tennessee, Knoxville, Tennessee, United States 116 University of Tokyo, Tokyo, Japan
117 University of Tsukuba, Tsukuba, Japan
119 V. Fock Institute for Physics, St. Petersburg State University, St. Petersburg, Russia 120 Variable Energy Cyclotron Centre, Kolkata, India
121 Vestfold University College, Tonsberg, Norway 122 Warsaw University of Technology, Warsaw, Poland 123 Wayne State University, Detroit, Michigan, United States
124 Wigner Research Centre for Physics, Hungarian Academy of Sciences, Budapest, Hungary 125 Yale University, New Haven, Connecticut, United States
126 Yonsei University, Seoul, South Korea
127 Zentrum f¨ur Technologietransfer und Telekommunikation (ZTT), Fachhochschule Worms, Worms, Germany
